Such a method and such an apparatus is known from U.S. Pat. No. 7,187,749 B2. The known apparatus is provided for dental panoramic and tomographic imaging. According to the known method and the known apparatus the motion of a patient is detected during the imaging process by accelerometers attached to a positioning device and the radiographic raw images are shifted to correct for the motion of the patient.
A disadvantage of the known method and the known apparatus is that the shifting of the radiographic raw images is only suitable for compensating translational movements. The lack of compensation for arbitrary movement of the patient during the imaging process may result in blurring of the views obtained by the image processing.
In the field of tomography, blurring by motion is a common problem. For limiting the blurring effects patient support systems are usually provided for the purpose of holding body parts of the patient as still as possible with respect to the X-ray apparatus. For instance, in dental panoramic X-ray systems, which are also arranged for dental tomography, a bite may be provided, on which the patient can bite during the entire acquisition to limit the motion of the patient. In alternative arrangements, the patient lies on a bed and the body parts are kept still with the help of radio transparent head cushions and belts. However, even these tools are not sufficient for suppressing the motion of the patient completely.
EP 1,815,794 A1 discloses a positioning method for dental radiology and linear tomography. For positioning the patient with respect to an X-ray imaging system a set of video cameras is used to put the patient in a given desired position for the examination.
KAK & SLANEY, Principle of Computerized Tomographic Imaging, SIAM Society, 2001 is a text book containing details on various reconstruction methods used in computer-tomography, in particular frequency based reconstruction methods and various algebraic methods, for instance the so called Algebraic Reconstruction Techniques (=ART) and its derivatives, especially the Simultaneous Iterative Reconstruction Technique (=SIRT) and Simultaneous Algebraic Reconstruction Technique (=SART).
A general review on computer-tomography can be found in KALEDENDER, W. A.: X-ray computed tomography in: Phys. Med. Biol. 51 (2006) R29-R43.
MICHEL, D.; FRÉDÉRIC; HIROYUKI, K.: Two-dimensional rebinning of helical cone-beam computerized tomography data using John's equation, Inverse Problems, Volume 19, Issue 6, pp. S41-S54, 2003 describes a rebinning method for compensating the deviation of an x-ray imaging system moving around an object on a helical path from a two-dimensional slice on which a crossectional view of the object is generated.
DOBBINS III, J. T. and GODFREY, D. J.: Digital X-ray tomosynthesis: current state of the art and clinical potential, Phys. Med. Biol. 48 (2003) R65-R106 describes various reconstruction methods used in tomosynthesis.
SHEPP, L. A. and VARDI Y.: Maximum Likelihood Reconstruction for Emission Tomography, IEEE Trans. Med. Im., Vol. 1, 113-122, 1982 describes the application of a maximum likelihood method in positron emission tomography.
GB 23 84 155 A describes a video system which is used to align tomographic images of a patient to a radiotherapy system so that the tomographic images can be used for controlling the beam of the radio-therapy-system.
US 2006/0149134 A1 discloses a visual assisted guidance of an endoscope for bronchoscopy.
The use of a maximum likelihood approach for the deconvolution of images taken by a CCD-camera is discussed in BENVENUTO, F. and LA CAMERA, A. et al.: Study of an iterative method for the reconstruction of images corrupted by Poisson and Gauss noise, Inverse Problems 24, 2008.
An overview on biometric systems is given in JAIN, A. K. and ROSS, A.: Multibiometric Systems, Comm. ACM, Special Issue on Multimodal Interfaces, vol. 47, no. 1, pp. 34-40, 2004.
WISKOTT, J. et al.: Face recognition by elastic bunch graph matching. In L. C. Jain et al., editor: Intelligent biometric techniques in fingerprints and face recognition, pp. 355-396. CRC Press, 1999 describe methods for face recognition.
Further information of face recognition can also be found in FERIS, R. S. et al.: Hierarchical wavelet networks for facial feature localization, IEEE International Conference on Automatic Face and Gesture Recognition, 2002, pp. 118-123.
MIDDENDORFF, C.; BOWEYER, K.; YAN, P.: Multi-Modal Biometrics Involving the Human Ear, Proc. IEEE Conf. CVPR 07, 2007 describes methods for detecting the human ear.
M A, Y. et al.: Robust precise eye location under probabilistic framework, IEEE International Conference on Automatic Face and Gesture Recognition, 2004, pp. 339-344 discloses methods for the detection of eyes.
DARGHAM, J. and CHEKIMA, A.: Lips Detection in the Normalised RGB Colour Scheme Proc. 2nd Conf. on Information and Communication technologies, ICCTA, 2006, pp. 1546-1551, 2006 contain methods for detecting the lips of a person.
FROSIO, I. and BORGHESE, N. A.: Real-time accurate circle fitting with occlusions, Vol. 41, pp. 101-114, 2008 describes a method for an accurate location of circles inside images in the presence of a partial occlusion.